Conventional call center technology and customer relationship management technology are often unable to provide call center representatives with a quick view into recent member activities on a customer facing system, where customer information and transactions are supplied across multiple communication channels. The data necessary to provide these functions is frequently generated and stored by disparate systems, where the data records needed for these features are often incompatible.
Conventional CRM and call center systems gather and process data to analyze customer information to provide a history how other prior representatives have helped a customer in the past. However, conventional systems may not be able to offer insight into what the member was doing through multiple communication channels, in real-time or near real-time. Moreover, conventional marketing tools merely cross-reference behavioral aspects of members against broad demographic grouping criteria to draw inferences about a member's particular behavior. But, such conventional tools are unable to identify marketing leads, in real-time or near-real time, based on a member's interactions with the systems, from across one or more of communication channels.
What is needed is a means of capturing information about multichannel communications and customer activities, which may be converted to a commonly understood format, and then stored for downstream applications to use for real-time multichannel understanding of customer activities, or data analysis.